Interpopulation Variations in Behavioral Syndromes of a Jumping Spider from Insecticide‐Treated and Insecticide‐Free Orchards
Bibliographic record
Abstract
Abstract Variations in environmental conditions can influence behavioral syndromes (correlated tendencies in behaviors), and understanding the factors that shape trait covariation is particularly relevant when species are challenged by environmental changes. We investigated how behavioral syndromes varied at extremes of a gradient of anthropogenic disturbance, using apple orchards with different histories of insecticidal applications as a model system. Eris militaris (Araneae: Salticidae) jumping spiders were sampled from an insecticide‐free orchard and an insecticide‐treated orchard from Southern Québec. Spiders were tested for activity, aggression, boldness, and voracity under standardized conditions. Behavioral syndrome structure was compared between the two populations using Bayesian multiresponse models and structural equation modeling. Syndrome structure differed significantly between the two populations. The insecticide‐free population showed evidence of a syndrome involving all measured traits, while only aggression, boldness and voracity were correlated in the insecticide‐treated population. The insecticide‐free population showed negative correlations between active and voracious behavioral types vs. aggressive and bold types while the insecticide‐treated population showed a negative correlation between aggression‐boldness and voracity. This research is a first step in investigating the impact of anthropogenic disturbances on behavioral syndromes and demonstrates that behavioral syndromes may vary with respect to insecticidal applications.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".